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/var/folders/8t/s1y_vz7x589_hpgh_gmsk1vr0000gn/T//RtmpJxujx7/downloaded_packagesinstall.packages("readxl")Error in install.packages : Updating loaded packagesinstall.packages("readxl")trying URL 'https://cran.rstudio.com/bin/macosx/el-capitan/contrib/3.6/readxl_1.3.1.tgz'
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/var/folders/8t/s1y_vz7x589_hpgh_gmsk1vr0000gn/T//RtmpSAgBw6/downloaded_packageslibrary(readxl)Task 4 - Decathlon Data
candy_2015 <- read_excel("boing-boing-candy-2015.xlsx")
candy_2015NAhead(candy_2015)dim(candy_2015)[1] 5630 124names(dim(candy_2015))NULLnames(candy_2015) [1] "Timestamp"
[2] "How old are you?"
[3] "Are you going actually going trick or treating yourself?"
[4] "[Butterfinger]"
[5] "[100 Grand Bar]"
[6] "[Anonymous brown globs that come in black and orange wrappers]"
[7] "[Any full-sized candy bar]"
[8] "[Black Jacks]"
[9] "[Bonkers]"
[10] "[Bottle Caps]"
[11] "[Box’o’ Raisins]"
[12] "[Brach products (not including candy corn)]"
[13] "[Bubble Gum]"
[14] "[Cadbury Creme Eggs]"
[15] "[Candy Corn]"
[16] "[Vials of pure high fructose corn syrup, for main-lining into your vein]"
[17] "[Candy that is clearly just the stuff given out for free at restaurants]"
[18] "[Cash, or other forms of legal tender]"
[19] "[Chiclets]"
[20] "[Caramellos]"
[21] "[Snickers]"
[22] "[Dark Chocolate Hershey]"
[23] "[Dental paraphenalia]"
[24] "[Dots]"
[25] "[Fuzzy Peaches]"
[26] "[Generic Brand Acetaminophen]"
[27] "[Glow sticks]"
[28] "[Broken glow stick]"
[29] "[Goo Goo Clusters]"
[30] "[Good N' Plenty]"
[31] "[Gum from baseball cards]"
[32] "[Gummy Bears straight up]"
[33] "[Creepy Religious comics/Chick Tracts]"
[34] "[Healthy Fruit]"
[35] "[Heath Bar]"
[36] "[Hershey’s Kissables]"
[37] "[Hershey’s Milk Chocolate]"
[38] "[Hugs (actual physical hugs)]"
[39] "[Jolly Rancher (bad flavor)]"
[40] "[Jolly Ranchers (good flavor)]"
[41] "[Kale smoothie]"
[42] "[Kinder Happy Hippo]"
[43] "[Kit Kat]"
[44] "[Hard Candy]"
[45] "[Lapel Pins]"
[46] "[LemonHeads]"
[47] "[Licorice]"
[48] "[Licorice (not black)]"
[49] "[Lindt Truffle]"
[50] "[Lollipops]"
[51] "[Mars]"
[52] "[Mary Janes]"
[53] "[Maynards]"
[54] "[Milk Duds]"
[55] "[LaffyTaffy]"
[56] "[Minibags of chips]"
[57] "[JoyJoy (Mit Iodine)]"
[58] "[Reggie Jackson Bar]"
[59] "[Pixy Stix]"
[60] "[Nerds]"
[61] "[Nestle Crunch]"
[62] "[Now'n'Laters]"
[63] "[Pencils]"
[64] "[Milky Way]"
[65] "[Reese’s Peanut Butter Cups]"
[66] "[Tolberone something or other]"
[67] "[Runts]"
[68] "[Junior Mints]"
[69] "[Senior Mints]"
[70] "[Mint Kisses]"
[71] "[Mint Juleps]"
[72] "[Mint Leaves]"
[73] "[Peanut M&M’s]"
[74] "[Regular M&Ms]"
[75] "[Mint M&Ms]"
[76] "[Ribbon candy]"
[77] "[Rolos]"
[78] "[Skittles]"
[79] "[Smarties (American)]"
[80] "[Smarties (Commonwealth)]"
[81] "[Chick-o-Sticks (we don’t know what that is)]"
[82] "[Spotted Dick]"
[83] "[Starburst]"
[84] "[Swedish Fish]"
[85] "[Sweetums]"
[86] "[Those odd marshmallow circus peanut things]"
[87] "[Three Musketeers]"
[88] "[Peterson Brand Sidewalk Chalk]"
[89] "[Peanut Butter Bars]"
[90] "[Peanut Butter Jars]"
[91] "[Trail Mix]"
[92] "[Twix]"
[93] "[Vicodin]"
[94] "[White Bread]"
[95] "[Whole Wheat anything]"
[96] "[York Peppermint Patties]"
[97] "Please leave any remarks or comments regarding your choices."
[98] "Please list any items not included above that give you JOY."
[99] "Please list any items not included above that give you DESPAIR."
[100] "Guess the number of mints in my hand."
[101] "Betty or Veronica?"
[102] "Check all that apply: \"I cried tears of sadness at the end of ____________\""
[103] "\"That dress* that went viral early this year - when I first saw it, it was ________\""
[104] "Fill in the blank: \"Taylor Swift is a force for ___________\""
[105] "What is your favourite font?"
[106] "If you squint really hard, the words \"Intelligent Design\" would look like."
[107] "Fill in the blank: \"Imitation is a form of ____________\""
[108] "Please estimate the degree(s) of separation you have from the following celebrities [JK Rowling]"
[109] "Please estimate the degree(s) of separation you have from the following celebrities [JJ Abrams]"
[110] "Please estimate the degree(s) of separation you have from the following celebrities [Beyoncé]"
[111] "Please estimate the degree(s) of separation you have from the following celebrities [Bieber]"
[112] "Please estimate the degree(s) of separation you have from the following celebrities [Kevin Bacon]"
[113] "Please estimate the degree(s) of separation you have from the following celebrities [Francis Bacon (1561 - 1626)]"
[114] "[Sea-salt flavored stuff, probably chocolate, since this is the \"it\" flavor of the year]"
[115] "[Necco Wafers]"
[116] "Which day do you prefer, Friday or Sunday?"
[117] "Please estimate the degrees of separation you have from the following folks [Bruce Lee]"
[118] "Please estimate the degrees of separation you have from the following folks [JK Rowling]"
[119] "Please estimate the degrees of separation you have from the following folks [Malala Yousafzai]"
[120] "Please estimate the degrees of separation you have from the following folks [Thom Yorke]"
[121] "Please estimate the degrees of separation you have from the following folks [JJ Abrams]"
[122] "Please estimate the degrees of separation you have from the following folks [Hillary Clinton]"
[123] "Please estimate the degrees of separation you have from the following folks [Donald Trump]"
[124] "Please estimate the degrees of separation you have from the following folks [Beyoncé Knowles]" view(candy_2015)Error in view(candy_2015) : could not find function "view"candy_2016 <- read_excel("boing-boing-candy-2016.xlsx")
candy_2016candy_2017 <- read_excel("boing-boing-candy-2017.xlsx")New names:
* `` -> ...114candy_2017candy_2015_clean <- candy_2015 %>%
select(c(2:96))
candy_2016_clean <- candy_2016 %>%
select(c(2:5,7:106))candy_2017_clean <- candy_2017 %>%
select(c(2:5,7:109))candy_2015_clean <- clean_names(candy_2015_clean)
candy_2016_clean <- clean_names(candy_2016_clean)
candy_2017_clean <- clean_names(candy_2017_clean)
#glimpse(candy_2015_clean)
#glimpse(candy_2016_clean)
#glimpse(candy_2017_clean)
#Data type
typeof(candy_2015_clean)[1] "list"typeof(candy_2016_clean)[1] "list"typeof(candy_2017_clean)[1] "list"candy_2015_clean$year = "2015"
candy_2016_clean$year = "2016"
candy_2017_clean$year = "2017"
candy_2015_clean$country = ''
candy_2015_clean$gender = ''
candy_2015_clean_reordered <- candy_2015_clean[, c(2, 98, 1, 97, 3:96)]
#view(candy_2015_clean_reordered)#View cleaned data
view(candy_2015_clean_reordered)
view(candy_2016_clean)
view(candy_2017_clean)
dim(candy_2015_clean_reordered)[1] 5630 98dim(candy_2016_clean)[1] 1259 105dim(candy_2017_clean)[1] 2460 108candy_2015_clean_long <- pivot_longer(data = candy_2015_clean_reordered[,1:98],
cols = 5:97,
names_to = "column_candy",
values_to = "value")
candy_2016_clean_long <- pivot_longer(data = candy_2016_clean[,1:105],
cols = 5:104,
names_to = "column_candy",
values_to = "value")
candy_2017_clean_long <- pivot_longer(data = candy_2017_clean[,1:108],
cols = 5:107,
names_to = "column_candy",
values_to = "value")
view(candy_2015_clean_long)view(candy_2016_clean_long)view(candy_2017_clean_long)
candy_all_years_clean <- rbind(candy_2015_clean_long,
candy_2016_clean_long,
candy_2017_clean_long)
view(candy_all_years_clean)